#-*- coding:UTF-8 -*-
import numpy as np
import cv2

# cap = cv2.VideoCapture(0)
# ret = cap.set(3, 640)  # 设置帧宽
# ret = cap.set(4, 480)  # 设置帧高
# font = cv2.FONT_HERSHEY_SIMPLEX  # 设置字体样式
# kernel = np.ones((5, 5), np.uint8)  # 卷积核

def detect(frame):

# if cap.isOpened() is True:  # 检查摄像头是否正常启动
#     while (True):
#     ret, frame = cap.read()
    font = cv2.FONT_HERSHEY_SIMPLEX  # 设置字体样式
    kernel = np.ones((5, 5), np.uint8)  # 卷积核
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)  # 转换为灰色通道
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)  # 转换为HSV空间

    lower_green = np.array([35, 50, 100])  # 设定绿色的阈值下限
    upper_green = np.array([77, 255, 255])  # 设定绿色的阈值上限
    #  消除噪声
    mask = cv2.inRange(hsv, lower_green, upper_green)  # 设定掩膜取值范围
    opening = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)  # 形态学开运算
    bila = cv2.bilateralFilter(mask, 10, 200, 200)  # 双边滤波消除噪声
    edges = cv2.Canny(opening, 50, 100)  # 边缘识别
    # 识别圆形
    circles = cv2.HoughCircles(
        edges, cv2.HOUGH_GRADIENT, 1, 100, param1=100, param2=40, minRadius=10, maxRadius=500)
    if circles is not None:  # 如果识别出圆
        for circle in circles[0]:
            #  获取圆的坐标与半径
            x = int(circle[0])
            y = int(circle[1])
            r = int(circle[2])
            cv2.circle(frame, (x, y), r, (0, 0, 255), 3)  # 标记圆
            cv2.circle(frame, (x, y), 3, (255, 255, 0), -1)  # 标记圆心
            text = 'x: ' + str(x) + '|y: ' + str(y)+"|r: " + str(r)
            print(text)
            cv2.putText(frame, text, (10, 30), font, 1, (0, 255, 0), 2, cv2.LINE_AA, 0)  # 显示圆心位置
            return text

    else:
        # 如果识别不出，显示圆心不存在
        cv2.putText(frame, 'x: None y: None', (10, 30), font, 1, (0, 255, 0), 2, cv2.LINE_AA, 0)
        print("no quan")
        return "NULL"
    cv2.imshow('frame', frame)
    cv2.imshow('mask', mask)
    cv2.imshow('edges', edges)
    k = cv2.waitKey(5) & 0xFF

    # if k == 27:
    #     break
    # cap.release()
    # cv2.destroyAllWindows()
# else:
#     print('cap is not opened!')